Dv. Budescu et al., A REVISED MODIFIED PARALLEL ANALYSIS FOR THE CONSTRUCTION OF UNIDIMENSIONAL ITEM POOLS, Applied psychological measurement, 21(3), 1997, pp. 233-252
Modified parallel analysis (MPA) is a heuristic method for assessing '
'approximate unidimensionality'' of item poors. It compares the second
eigenvalue of the observed correlation matrix with the corresponding
eigenvalue extracted from a ''parallel'' matrix generated by a unidime
nsional and locally independent model. Revised MPA (RMPA) generalizes
MPA and alleviates some of its technical limitations. RMPA includes an
important and useful feature for eliminating items that violate the t
est's unidimensionality. This is achieved by eliminating items, one at
a time, to determine their contribution to the matrices' eigenvalues.
A test for detecting items with large impact in the observed dataset
and then eliminating them is proposed. The new method was tested in se
veral simulations in which unidimensional item pools were ''contaminat
ed'' by various proportions of items from a secondary pool. The result
s indicate that RMPA does an excellent job of detecting low (10%) and
moderate (25%) levels of contamination, but fails in cases of maximal
(50%) contamination.